Live opening · Posted 7 hours ago
AI Central - Measurement and Reporting Engineer
Zensar Technologies · India
You are 7 hours behind. JobBeeper subscribers saw this role while it was still new.
At a glance
The key details from the original listing.
CompanyZensar Technologies
LocationIndia
SkillsPython, GraphQL, Power BI
Source
Oracle
Listed7 hours ago
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About the role
Description supplied by the original job listing.
SQL, Python for data pipelines, and a reporting layer — Power BI preferred
• GitHub data extraction via REST and GraphQL APIs: pull-request lifecycle, review events, Actions run telemetry. Must be able to derive merge rate, review cycle time and reviewer effort per pull request.
• ServiceNow reporting and data extraction, specifically the Vulnerability Response module and Application Vulnerable Item records; ServiceNow Table and REST APIs.
• Jira extraction and defect metrics at product grain.
• Engineering-metrics literacy (DORA or equivalent) and the judgment to distinguish an activity count from an outcome.
• Able to build an attribution model that records how a finding was closed — by agent, by tooling, or manually.
Nice To Have
Planview or comparable resource/time systems.
• GitHub Copilot usage and telemetry APIs.
• Dimensional data modeling.
• Experience instrumenting a program that was under scrutiny, where the numbers were contested.
Nice To Have
Planview or comparable resource/time systems.
• GitHub Copilot usage and telemetry APIs.
• Dimensional data modeling.
• Experience instrumenting a program that was under scrutiny, where the numbers were contested.
SQL, Python for data pipelines, and a reporting layer — Power BI preferred
• GitHub data extraction via REST and GraphQL APIs: pull-request lifecycle, review events, Actions run telemetry. Must be able to derive merge rate, review cycle time and reviewer effort per pull request.
• ServiceNow reporting and data extraction, specifically the Vulnerability Response module and Application Vulnerable Item records; ServiceNow Table and REST APIs.
• Jira extraction and defect metrics at product grain.
• Engineering-metrics literacy (DORA or equivalent) and the judgment to distinguish an activity count from an outcome.
• Able to build an attribution model that records how a finding was closed — by agent, by tooling, or manually.
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